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Better Physical Activity Classification using Smartphone Acceleration Sensor

  • Mobile Systems
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

Obesity is becoming one of the serious problems for the health of worldwide population. Social interactions on mobile phones and computers via internet through social e-networks are one of the major causes of lack of physical activities. For the health specialist, it is important to track the record of physical activities of the obese or overweight patients to supervise weight loss control. In this study, acceleration sensor present in the smartphone is used to monitor the physical activity of the user. Physical activities including Walking, Jogging, Sitting, Standing, Walking upstairs and Walking downstairs are classified. Time domain features are extracted from the acceleration data recorded by smartphone during different physical activities. Time and space complexity of the whole framework is done by optimal feature subset selection and pruning of instances. Classification results of six physical activities are reported in this paper. Using simple time domain features, 99 % classification accuracy is achieved. Furthermore, attributes subset selection is used to remove the redundant features and to minimize the time complexity of the algorithm. A subset of 30 features produced more than 98 % classification accuracy for the six physical activities.

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Acknowledgement

This research was supported by the NSTIP strategic technologies program (12-INF2290-10) in the Kingdom of Saudi Arabia.

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Authors and Affiliations

  1. Department of Computer Science College of Computer and Information systems, Umm-Alqura University, Makkah, Saudi Arabia

    Muhammad Arif, Mohsin Bilal & Ahmed Kattan

  2. Ubicomp Lab Department of Mathematics, Statistics and Computer Science, Marquette University, 1250 W Wisconsin Ave, Milwaukee, WI, 53233, USA

    S. Iqbal Ahamed

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  1. Muhammad Arif
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  2. Mohsin Bilal
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  3. Ahmed Kattan
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  4. S. Iqbal Ahamed
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Correspondence to Muhammad Arif.

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This article is part of the Topical Collection on Mobile Systems

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Arif, M., Bilal, M., Kattan, A. et al. Better Physical Activity Classification using Smartphone Acceleration Sensor. J Med Syst 38, 95 (2014). https://doi.org/10.1007/s10916-014-0095-0

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  • DOI: https://doi.org/10.1007/s10916-014-0095-0

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